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BF1: A Causal Dyadic Sparse-Attention Retrofit for Efficient Long-Context Transformers
Not provided in the abstract
sparse attentionlong-context transformersmodel optimization
2608.20427
Builder Relevance
2h ago80%
Abstract
BF1 introduces a sparse-attention mechanism that significantly improves the efficiency of long-context transformers.
Reality Card
Core Claim
BF1 achieves a 10.91x per-layer prefill speedup for dense attention between 2K and 4K tokens on an NVIDIA RTX PRO 6000 GPU.
Method / Result
Reduces warm whole-model time to first token by up to 15.3% at 32K tokens.
Limitations
The performance gains are tied to specific hardware and may not generalize across different architectures.
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